Model CoverageVision Language Models (VLMs)

Ministral3 VL

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Ministral3 is Mistral AI’s efficient small model series. The vision-capable variants support image-text inputs for multimodal tasks.

TaskImage-Text-to-Text
ArchitectureMistral3ForConditionalGeneration
Parameters3B – 14B
HF Orgmistralai

Available Models

  • Ministral-3-14B-Instruct-2512
  • Ministral-3-8B-Instruct-2512
  • Ministral-3-3B-Instruct-2512

Architecture

  • Mistral3ForConditionalGeneration

Example HF Models

ModelHF ID
Ministral-3 3B Instructmistralai/Ministral-3-3B-Instruct-2512
Ministral-3 8B Instructmistralai/Ministral-3-8B-Instruct-2512
Ministral-3 14B Instructmistralai/Ministral-3-14B-Instruct-2512

Example Recipes

RecipeDatasetDescription
ministral3_3b_medpix.yamlMedPix-VQASFT — Ministral3 3B on MedPix
ministral3_8b_medpix.yamlMedPix-VQASFT — Ministral3 8B on MedPix
ministral3_14b_medpix.yamlMedPix-VQASFT — Ministral3 14B on MedPix

Try with NeMo AutoModel

1. Install (full instructions):

$pip install nemo-automodel

2. Clone the repo to get the example recipes:

$git clone https://github.com/NVIDIA-NeMo/Automodel.git
$cd Automodel

3. Run the recipe from inside the repo:

$automodel --nproc-per-node=8 examples/vlm_finetune/mistral/ministral3_3b_medpix.yaml

1. Pull the container and mount a checkpoint directory:

$docker run --gpus all -it --rm \
>  --shm-size=8g \
>  -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
>  nvcr.io/nvidia/nemo-automodel:26.04.00

2. Navigate to the AutoModel directory (where the recipes are):

$cd /opt/Automodel

3. Run the recipe:

$automodel --nproc-per-node=8 examples/vlm_finetune/mistral/ministral3_3b_medpix.yaml

See the Installation Guide and VLM Fine-Tuning Guide.

Fine-Tuning

See the VLM Fine-Tuning Guide.

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